As cities grow and public infrastructure expands, it becomes increasingly necessary to search, catalog, and monitor the public infrastructure (e.g., buildings, vegetation, artifacts, street signs, etc.). Spatial databases (so-called Geographic Information Systems (GIS)) are an essential tool for public service departments, city managers and urban planners. They face the need to set up and maintain inventories not only of trees, but also other object classes like street signs, utility poles, or street furniture, to facilitate urban planning, citizen safety, and emergency response plans.
However, the process of cataloging and classifying visible objects in the public space (e.g. street signs, building facades, fire hydrants, solar panels and mail boxes) is a difficult endeavor. Currently, such objects are mapped manually by professional surveyors in labor-intensive and costly field campaigns (e.g., using expensive ad-hoc imagery such as LiDAR). In many cases, the information is not captured or analyzed at all, due to the cost, time, and organizational headache it involves.